Principal Enterprise Data Architect

Smarsh•Atlanta, NY

14d

About The Position

We are seeking a highly experienced enterprise data architect to own and drive our company’s data architecture, data model, master data governance and analytics platform. You will be responsible for defining the enterprise data model and entity relationships across our business systems (including COTS ERPs such as Salesforce, NetSuite and our proprietary telemetry/usage systems and internal software) and for governing master data and enterprise metadata. You will lead the architecture and implementation of our data lake / data-warehouse environment (e.g., Snowflake) and be an expert in leveraging tools (including AI offerings such as Cortex or other advanced AI platforms). You will also own enterprise operational and financial reporting and analytics, leading a team to deliver high-quality insights and visualizations to drive business decisions. This is a strategic role in a fast-growing SaaS company (~$500M revenue) and you will be a key leader for data-driven growth.

Requirements

10-15+ years’ experience in data architecture / enterprise data management roles (in mid-to large organizations).
Proven experience working in a SaaS software company (ideally ~$200M-$1B revenue) or similar high-growth technology company.
Deep experience architecting enterprise data models and entity-relationship designs across multiple systems and domains (customer, product, usage/telemetry, finance, operations).
Hands-on and strategic experience with data lake / data warehouse platforms—experience with Snowflake is strongly required.
Experience ingesting and integrating data from CRM systems (Salesforce), ERP systems (NetSuite), Atlassian tools (Jira/Confluence), and product telemetry / usage data systems.
Strong experience in master data management (MDM) and governance, metadata management, data quality frameworks, data cataloging and data lineage.
Expertise in analytics and visualization leadership: delivering enterprise reporting, dashboards, KPI frameworks, business partner engagement.
Excellent leadership, communication and stakeholder management skills: able to translate business needs into data architecture and analytics solutions and lead a team.
A Bachelor’s Degree in Computer Science, Information Systems, Data Science, or related field (Master’s preferred) and relevant certifications (e.g., CDMP, TOGAF, or Snowflake certifications) are helpful.
Strong understanding of security, compliance and data governance in enterprise contexts.

Nice To Haves

Experience evaluating and deploying AI/SQL tools, augmented analytics and working with data science/AI teams to operationalize insights (experience with Cortex or comparable tools is a plus).

Responsibilities

Define, maintain and evolve the Enterprise Data Model and entity-relationship architecture across all business systems: CRM/ERP (Salesforce), ERP (NetSuite), Atlassian tools (Jira/Confluence), proprietary product telemetry/usage data, as well as other internal systems.
Own master data governance : establish policies, standards, ownership/responsibility, definitions, data quality metrics, and lifecycle management for master entities (e.g., Customer, Account, Product, Usage, Finance, Vendor, Employee) and establishing “golden data”.
Lead and manage the data lake / data warehouse architecture , with primary platform Snowflake and supporting data-ingestion / ETL/ELT pipelines, streaming usage data, telemetry, business system feeds, and operational/financial data.
Stay on the cutting-edge of AI, SQL, analytics: evaluate and adopt AI-SQL tools (e.g., Cortex or similar), support augmented analytics , facilitate self-service data/analytics for business users, and embed AI/workbench capabilities into the data platform.
Own and lead a team responsible for enterprise operational and financial reporting & analytics : define KPIs, build dashboards, develop visualization strategy (e.g., Power BI, Tableau, Looker), ensure data accuracy, timeliness and scalability.
Partner cross-functionally with business systems owners (Salesforce, NetSuite, product telemetry, Atlassian), IT, data engineering, finance, sales, operations and product leadership to ensure alignment of data strategy with business strategy.
Enforce data governance, metadata management, data lineage, usage tracking, data cataloging, and ensure compliance with applicable standards/regulations (e.g., GDPR, CCPA, SOX where applicable).
Define and monitor data quality, data security, access controls, and ensure platform scalability, performance and reliability.
Provide thought leadership on data architecture best practices, mentor senior data & analytics engineers, promote a data-driven culture across the company.
Develop roadmaps for data architecture, analytics platform evolution, cost control and performance optimization.